Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	Louisiana	30,322
2	Florida	27,404
3	Arizona	26,969
4	Mississippi	25,351
5	Alabama	22,933
6	New York	22,233
7	Georgia	21,689
8	New Jersey	21,431
9	South Carolina	21,232
10	Nevada	20,680
11	Texas	20,280
12	Tennessee	19,968
13	Rhode Island	19,701
14	District of Columbia	19,084
15	Arkansas	18,147
16	Massachusetts	18,096
17	Iowa	17,322
18	Delaware	17,168
19	Maryland	17,089
20	Illinois	17,038
21	California	16,539
22	Idaho	16,368
23	Nebraska	16,205
24	Utah	15,004
25	Connecticut	14,425
26	North Carolina	14,344
27	Virginia	12,988
28	Oklahoma	12,804
29	Indiana	12,664
30	Kansas	12,558
31	Wisconsin	12,556
32	North Dakota	12,132
33	South Dakota	12,084
34	Minnesota	11,942
35	Missouri	11,905
36	New Mexico	11,422
37	Michigan	10,490
38	Pennsylvania	10,290
39	Kentucky	9,854
40	Ohio	9,581
41	Washington	9,492
42	Colorado	9,430
43	Puerto Rico	9,032
44	Alaska	7,285
45	Wyoming	5,992
46	Oregon	5,731
47	Montana	5,702
48	New Hampshire	5,184
49	West Virginia	5,058
50	Hawaii	4,111
51	Maine	3,187
52	Vermont	2,463

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Mississippi	340
2	Georgia	265
3	North Dakota	260
4	Alabama	234
5	Tennessee	225
6	Texas	218
7	Puerto Rico	217
8	Idaho	212
9	Florida	194
10	Iowa	192
11	Arkansas	186
12	Nevada	181
13	Kentucky	180
14	Missouri	175
15	Louisiana	168
16	Oklahoma	164
17	California	156
18	Illinois	156
19	South Carolina	153
20	Hawaii	148
21	North Carolina	143
22	Nebraska	135
23	Virginia	134
24	Wisconsin	132
25	South Dakota	124
26	Utah	121
27	Kansas	119
28	Indiana	116
29	Maryland	112
30	Arizona	104
31	Alaska	101
32	Minnesota	94
33	Rhode Island	94
34	District of Columbia	92
35	Montana	88
36	Ohio	83
37	West Virginia	80
38	Wyoming	78
39	Washington	77
40	New Mexico	71
41	Michigan	63
42	Delaware	62
43	Oregon	56
44	Colorado	53
45	Pennsylvania	53
46	Massachusetts	42
47	New York	32
48	New Jersey	28
49	Maine	21
50	Connecticut	15
51	New Hampshire	11
52	Vermont	5

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	1,793
2	New York	1,668
3	Massachusetts	1,289
4	Connecticut	1,250
5	Louisiana	997
6	Rhode Island	970
7	District of Columbia	852
8	Mississippi	735
9	Michigan	664
10	Arizona	644
11	Illinois	636
12	Delaware	611
13	Maryland	607
14	Pennsylvania	594
15	Indiana	473
16	Florida	467
17	South Carolina	466
18	Georgia	451
19	Alabama	402
20	Texas	388
21	Nevada	381
22	New Mexico	350
23	Ohio	336
24	Colorado	331
25	Iowa	322
26	Minnesota	317
27	New Hampshire	314
28	California	298
29	Virginia	285
30	Washington	252
31	Missouri	245
32	North Carolina	238
33	Tennessee	215
34	Arkansas	212
35	Kentucky	197
36	Nebraska	194
37	Wisconsin	184
38	Oklahoma	179
39	South Dakota	177
40	North Dakota	175
41	Idaho	167
42	Kansas	145
43	Utah	119
44	Puerto Rico	117
45	Oregon	97
46	Maine	95
47	West Virginia	94
48	Vermont	92
49	Montana	83
50	Wyoming	58
51	Alaska	36
52	Hawaii	31

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Mississippi	10
2	Nevada	10
3	Arizona	8
4	Florida	7
5	Louisiana	7
6	South Carolina	7
7	Texas	7
8	Georgia	5
9	Arkansas	4
10	Idaho	4
11	Puerto Rico	4
12	Tennessee	4
13	Alabama	3
14	California	3
15	Iowa	3
16	Kentucky	3
17	North Carolina	3
18	Oklahoma	3
19	District of Columbia	2
20	Indiana	2
21	Massachusetts	2
22	Missouri	2
23	Montana	2
24	Nebraska	2
25	New Mexico	2
26	Ohio	2
27	Washington	2
28	Hawaii	1
29	Illinois	1
30	Kansas	1
31	Maryland	1
32	Michigan	1
33	Minnesota	1
34	New Hampshire	1
35	North Dakota	1
36	Oregon	1
37	Pennsylvania	1
38	Rhode Island	1
39	South Dakota	1
40	Utah	1
41	Virginia	1
42	West Virginia	1
43	Wisconsin	1
44	Alaska	0
45	Colorado	0
46	Connecticut	0
47	Delaware	0
48	Maine	0
49	New Jersey	0
50	New York	0
51	Vermont	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	140,819	1	99
Lafayette	Florida	134,054	2	99
Lake	Tennessee	115,308	3	99
Lee	Arkansas	111,324	4	99
Lincoln	Arkansas	104,423	5	99
Davidson	Tennessee	35,962	144	95
Richland	South Carolina	23,285	406	87
Orange	California	14,150	938	70
York	South Carolina	13,852	972	69
Pierce	Washington	7,733	1718	45

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Hancock	Georgia	4,375	1	99
Galax city	Virginia	4,096	2	99
Randolph	Georgia	3,836	3	99
Terrell	Georgia	3,517	4	99
Neshoba	Mississippi	3,331	5	99
Richland	South Carolina	431	674	78
Davidson	Tennessee	349	828	73
Orange	California	262	1050	66
Pierce	Washington	186	1333	57
York	South Carolina	114	1694	46

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.